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Abstract: Streaming data is growing in prevalence as connectivity increases and data streaming sources proliferate. But getting precisely the data one needs from data streams can be difficult. Given the low resource capabilities of some clients, the decision process of which data to keep often must be made `upstream' of the client. We postulate that the popularity of SQL for querying relational databases makes the language a viable solution to retrieving data from data streams. In response, we have... (Update)
Context of citations to this paper: More
.... rem PJ maybe yes any trt irt stats inter D O G S Telegraph [11] op or parl no yes any trt stats l dr intra D O L S dQUOB [21, 22] op or no no no ac statstrt stats inter D L A Table 1. Properties of existing adaptive query processing techniques (PPHJs) is proposed in [20]...
.... an example being filtering to transmit only those data items that are actually currently viewed in a remote scientific visualization [9, 12]; 2) they address multimedia applications, by executing scheduling algorithms that reduce data by discarding packets based on loss...
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BibTeX entry: (Update)
PLALE, B., AND SCHWAN, K. Optimizations enabled by a relational data model view to querying data streams. In IEEE International Parallel and Distributed Processing Symposium (IPDPS) (April 2001). http://citeseer.ist.psu.edu/article/plale01optimizations.html More
@inproceedings{ plaleoptimizations,
author = "Beth Plale and Karsten Schwan",
title = "Optimizations Enabled by Relational Data Model View to Querying Data Streams",
pages = "20--20",
url = "citeseer.ist.psu.edu/article/plale01optimizations.html" }
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